Hand Gesture Recognition System (HGRS) for detection of American Sign Language (ASL) alphabets has become essential tool for specific end users (i.e. hearing and speech impaired) to interact with general users via com...
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ISBN:
(纸本)9781509037551
Hand Gesture Recognition System (HGRS) for detection of American Sign Language (ASL) alphabets has become essential tool for specific end users (i.e. hearing and speech impaired) to interact with general users via computer system. ASL has been proved to be a powerful and conventional augmentative communication tool especially for specific users. ASL consists of 26 primary letters, of which 5 are vowels and 21 are consonants. Proposed Real-time static Alphabet American Sign Language Recognizer-(A-ASLR) is designed for the recognition of ASL alphabets into their translated version in text (i.e. A to Z). The architecture of A-ASLR system is fragmented into six consequent phases namely;image capturing, image pre-processing, region extraction, feature extraction, feature matching and pattern recognition. We have used Edge Orientation Histogram (EOH) in A-ASLR system. The system is developed for detection of ASL alphabets based on vision-based approach. It works without using colored gloves or expensive sensory gloves on hand. Our A-ASLR system achieves the recognition rate of 88.26% within recognition time of 0.5 second in complex background with mixed lightning condition.
Stereo image matching is one of the research areas in computervision. In stereo image matching, technological developments advances from area based matching techniques to the feature based matching techniques. In thi...
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ISBN:
(纸本)9781509020805
Stereo image matching is one of the research areas in computervision. In stereo image matching, technological developments advances from area based matching techniques to the feature based matching techniques. In this paper, we present a Harris corner detection algorithm for stereo image feature matching. This is an intensity based feature matching algorithm and it controls the strong and weak corners with the help of threshold value. Generally imageprocessing algorithms are simulated in software but to do hardware co-simulation, here the model based design is implemented in Xilinx System Generator. Further the architecture is synthesized on the Xilinx Virtex - 5 FPGA. Simulation results are included in this paper to verify the performance of proposed system. Complexity level is minimized in model based design than that of script level design.
A technique of formation of the effective features for the identification of regions of interest (ROI) in fundus images during laser coagulation is proposed. The technique is based on the texture analysis of selected ...
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ISBN:
(纸本)9783319464183
A technique of formation of the effective features for the identification of regions of interest (ROI) in fundus images during laser coagulation is proposed. The technique is based on the texture analysis of selected image patterns. The analysis of informative value of obtained feature space and the selection of the most effective features is performed using the data discriminative analysis. The best values of image fragmentation dimensions for the image segmentation and the feature sets providing the precise identification required for regions of interest are determined herein.
Convolutional Neural Networks (CNNs) are superior to fully connected neural networks in various speech recognition tasks and the advantage is pronounced in noisy environments. In recent years, many techniques have bee...
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ISBN:
(纸本)9781479999880
Convolutional Neural Networks (CNNs) are superior to fully connected neural networks in various speech recognition tasks and the advantage is pronounced in noisy environments. In recent years, many techniques have been proposed in the computervision community to improve CNN's classification performance. This paper considers two approaches recently developed for image classification and examines their impacts on noisy speech recognition performance. The first approach is to increase the depth of convolution layers. Different approaches to deepening the CNNs are compared. In particular, the usefulness of learning dynamic features with small convolution layers that perform convolution in time is shown along with a modulation frequency analysis of the learned convolution filters. The second approach is to use trainable activation functions. Specifically, the use of a Parametric Rectified Linear Unit (PReLU) is investigated. Experimental results show that both approaches yield significant improvements in performance. Combining the two approaches further reduces recognition errors, producing a word error rate of 11.1% in the Aurora4 task, the best published result for this corpus, with a standard one-pass bi-gram decoding set-up.
Serial number is a unique number given to a product which can be used for product identification and inventory management. Information about the product may be its manufacturing date, expiry date, place of manufacture...
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ISBN:
(纸本)9781509007745
Serial number is a unique number given to a product which can be used for product identification and inventory management. Information about the product may be its manufacturing date, expiry date, place of manufacture and so on. Some companies use serial numbers to keep track on the number of products which a retailer is authorized to sell. Thus serial number identification becomes an important part at industry level. This paper presents an approach to detect and identify serial numbers using computervision. Webcam is used to provide vision capability and Raspberry Pi which is Linux based system on chip hardware acts as the processing unit for this project making it a compact system. Various algorithms of OpenCV along with C++ language were used to extract numbers from the image. These numbers were later stored in a file to keep track of them.
We present COVERAGE a novel database containing copy move forged images and their originals with similar but genuine objects. COVERAGE is designed to highlight and address tamper detection ambiguity of popular methods...
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ISBN:
(纸本)9781467399616
We present COVERAGE a novel database containing copy move forged images and their originals with similar but genuine objects. COVERAGE is designed to highlight and address tamper detection ambiguity of popular methods, caused by self-similarity within natural images. In COVERAGE, forged original pairs are annotated with (i) the duplicated and forged region masks, and (ii) the tampering factor/similarity metric. For benchmarking, forgery quality is evaluated using (i) computervision-based methods, and (ii) human detection performance. We also propose a novel sparsity-based metric for efficiently estimating forgery quality. Experimental results show that (a) popular forgery detection methods perform poorly over COVERAGE, and (b) the proposed sparsity based metric best correlates with human detection performance. We release the COVERAGE database to the research community.
image enhancement (IE) methods present as a preprocessing step in object detection and recognition in computervision applications. The excellence of underwater images is negative in view that of precise propagation r...
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In India where roads carry about 87% of passenger traffic and 61% of freight traffic, makes maintenance and management of roads extremely important. Use of Machine vision to analyze street surface anomalies will help ...
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Despite recent advances in computervision humans still perform recognition of a novel scene in a single glance better than the best of the available systems. Consequently in order to achieve a similar ability in arti...
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